code: def output_markdown(filename, **kwargs):
      """
      Write the output of an analysis to a file.
      """
      with codecs.open(filename, "at") as outfile:
          text = "\n*** \n\n"
          text += "{} \n\n".format(time.strftime("%d/%m/%Y, %H:%M"))
          for k in sorted(kwargs):
              if isinstance(kwargs[k], dict):
                  dictionary = kwargs[k]
                  text += f"  - **{k}:**\n"
                  for entry in sorted(dictionary):
                      text += f"    - {entry}: {dictionary[entry]} \n"
              elif isinstance(kwargs[k], list):
                  text += f"  - **{k}:**\n"
                  for entry in kwargs[k]:
                      text += f"    - {entry}\n"
              else:
                  text += f"  - **{k}:** {kwargs[k]} \n"
          outfile.write(text)
  
imports: import codecs
  import csv
  import json
  import pickle
  import random
  import re
  import sys
  import time
  from copy import deepcopy
  import nltk
  from nltk.corpus import CategorizedPlaintextCorpusReader
  from nltk.data import load
  from nltk.tokenize.casual import EMOTICON_RE
label_desc: Use image node_id 5 for calling a global function with example usage: output_markdown(filename) without return types